As demonstrated in [1]}, the bounded dependence central limit theorem of [2]} can sometimes be used to show asymptotic normality if the random quantity can be written as sum of terms that each depend on only a small subset of the entries in \(X\) . To apply this theorem to our estimands, we will often need to use linearization to account for normalizing factors that depend on \(X\) .
